Edge intelligent agent cooperative-based charging pile cluster dynamic scheduling method and system

Abstract

The application provides a charging pile cluster dynamic scheduling method and system based on edge agent cooperation, and relates to the technical field of intelligent management of charging facilities. The problems of dependence of the existing system on centralized decision and stable communication, poor robustness in extreme environment, lack of accurate battery aging evaluation and multi-target cooperative optimization capability are solved. The method comprises the following steps: obtaining multi-dimensional monitoring data; dividing the cluster into monitoring and scheduling units, and calculating the port health index; screening high-priority units according to the health index, emergency discharge capacity and battery aging confidence interval; switching the scheduling mode according to the communication state and weather warning, and optimizing the scheduling by using a multi-agent cooperative algorithm; and generating and executing the scheduling instruction. The application improves the scheduling robustness, equipment life and overall efficiency in extreme scenarios.

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